Hi,
I am trying to use ALS.trainImplicit method in the
pyspark.mllib.recommendation. However it didn't work. So I tried use the
example in the python API documentation such as:
/r1 = (1, 1, 1.0)
r2 = (1, 2, 2.0)
r3 = (2, 1, 2.0)
ratings = sc.parallelize([r1, r2, r3])
model = ALS.trainImplicit(ratings, 1) /
It didn't work neither. After searching in google, I found that there are
only two overloads for ALS.trainImplicit in the scala script. So I tried
/model = ALS.trainImplicit(ratings, 1, 1)/, it worked. But if I set the
iterations other than 1, /model = ALS.trainImplicit(ratings, 1, 2)/ or
/model = ALS.trainImplicit(ratings, 4, 2)/ for example, it generated error.
The information is as follows:
count at ALS.scala:314
Job aborted due to stage failure: Task 6 in stage 189.0 failed 4 times, most
recent failure: Lost task 6.3 in stage 189.0 (TID 626,
ip-172-31-35-239.ec2.internal): com.esotericsoftware.kryo.KryoException:
java.lang.ArrayStoreException: scala.collection.mutable.HashSet
Serialization trace:
shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
org.apache.spark.scheduler.Task.run(Task.scala:54)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
It is really strange, because count at ALS.scala:314 is already out the loop
of iterations. Any idea?
Thanks a lot for advance.
FYI: I used spark 1.1.0 and ALS.train() works pretty well for all the cases.
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